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  2. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

  3. Cohen's h - Wikipedia

    en.wikipedia.org/wiki/Cohen's_h

    It can be used in calculating the sample size for a future study. When measuring differences between proportions, Cohen's h can be used in conjunction with hypothesis testing . A " statistically significant " difference between two proportions is understood to mean that, given the data, it is likely that there is a difference in the population ...

  4. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    Steps for using sample size tables: Postulate the effect size of interest, α, and β. Check sample size table [20] Select the table corresponding to the selected α; Locate the row corresponding to the desired power; Locate the column corresponding to the estimated effect size. The intersection of the column and row is the minimum sample size ...

  5. Sampling error - Wikipedia

    en.wikipedia.org/wiki/Sampling_error

    Toggle the table of contents. ... Print/export Download as PDF; Printable version; In other projects ... Sample Size Determination

  6. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    If the sample size is 1,000, then the effective sample size will be 500. It means that the variance of the weighted mean based on 1,000 samples will be the same as that of a simple mean based on 500 samples obtained using a simple random sample.

  7. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Print/export Download as PDF; Printable version; In other projects ... Contingency table, sample size > ca. 60, [1] any cell content ≥ 5, [13]

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  9. Estimation statistics - Wikipedia

    en.wikipedia.org/wiki/Estimation_statistics

    Estimation statistics, or simply estimation, is a data analysis framework that uses a combination of effect sizes, confidence intervals, precision planning, and meta-analysis to plan experiments, analyze data and interpret results. [1]